The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare program, which could be mitigated using lessons from machine learning.

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...

Deep learning finds numerous applications in machine vision solutions, particularly in enhancing image analysis and recognition tasks. Algorithmic models can be trained to recognize patterns, shapes ...

Smartwatches are among the wearable devices that gather health data. Translating that data into useful information can be complicated and expensive. (iStock) The human body constantly generates a ...

Discover how financial platforms build machine learning pipelines, create synthetic features, cut fraud, and manage development costs effectively.

REMA TIP TOP mechatronics engineer Rachael Laudehr delved into understanding how to detect conveyor roller failures earlier ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...

Three new books warn against turning into the person the algorithm thinks you are. Like a lot of Netflix subscribers, I find that my personal feed tends to be hit or miss. Usually more miss. The ...